An electricity grid is an interconnected network for delivering electricity from suppliers to consumers. It consists of generating stations that produce electrical power, high-voltage transmission lines that carry power from distant sources to demand centers, and distribution lines that connect individual customers. The Smart Grid, regarded as the next generation power grid, uses two-way flows of electricity and information to create a widely distributed automated energy delivery network. The objective of a smart grid is to modernize the transmission and distribution of electricity to allow for facilitating greater competition between providers, enabling greater use of variable energy sources (distributed generation), establishing the automation and monitoring capabilities needed for bulk transmission at greater distances, and enabling the use of market forces to drive energy conservation. Some of the main variables that will define a smart grid system include optimizing electricity usage for on and off peak periods, creating greater integration with distributed generation resources, e.g., solar panel, wind power, advanced monitoring for supply and demand of electricity, increased metering of household appliances, and developing communication systems within grid operations that increase transparency and control.
Current and future electricity grids are facing a continuous increase of fluctuating renewable power resources such as wind turbines and photovoltaic generators on a central as well as on a decentralized level resulting in additional balancing effort. Accordingly information and communications technology needs to be developed for coordination in a smart electricity grid. In essence, stable power system operation comes down to keeping a dynamic balance between power supply (by generators) and power consumption (by loads) under the physical limitations of the interconnecting power transmission and distribution network.
Demand-side-managements systems, also known for example as the power matcher, are designed to keep a dynamic balance between power supply and power consumption. But such systems do not account for the physical limitations of the power transmission and distribution network.
Examples for such demand-side-systems can be found, for example, in US2013015713, US2004039490, and EP2159749.
In the past, extension of demand-side management systems have been proposed, which utilize grid constraints information to calculate balances that take physical limitations of the grid into account. But the electricity grid is a shared medium hosting many different aggregators and/or retailers of electricity and, thus, it is very difficult if not impossible to impose that every aggregator and/or retailer will correctly take grid constraints into account. Furthermore, questions of which grid constraints will be taken into account by which aggregator and/or retailer and how to arrange that every aggregator and/or retailer gets a fair share have to be solved. Moreover, solving these fundamental issues may involve very large sets of data being passed between the operators of the electrical grid and the aggregators and/or retailers of the electricity as the congestion level is local. Also, congestion of the grid would need to be indicated for every of the endpoints controlled by a particular aggregator and/or retailer and constantly updated as the congestion levels change.
While it is clear that demand-side-management systems can deal with grid constraints, it is not clear how this can work in an open market with multiple aggregators and/or retailers each using their own demand-side-management system and all acting on the same electricity grid.
The introduction of demand response leads to a changed load on the electricity grid, since activating flexibility involves the modification of the consumed or generated power, in reaction to control signals issued by the user of the flexibility, e.g. an aggregator, BRP, DSO or TSO. Uninformed use of demand response, without taking into account the potential conflict of interests of all stakeholders involved, may also lead to emergency situations. A grid in emergency is a grid in which it is impossible to transfer electricity without provoking system instability or causing damage, and should be avoided.
For example, a BRP may activate flexibility to maintain the balance within its portfolio, in the form of a request for demand increase. When all available sources of flexibility are located in one part of the distribution network, the simultaneous behaviour of the activated flexibility sources may lead to local violations of network constraints, causing congestion, deteriorated voltage quality, etc. In this case, demand response becomes a provoker rather than a solver of problems in the electricity system.